20240013801. AUDIO CONTENT SEARCHING IN MULTI-MEDIA simplified abstract (Getac Technology Corporation)
Contents
AUDIO CONTENT SEARCHING IN MULTI-MEDIA
Organization Name
Inventor(s)
Muhammad Adeel of Edina MN (US)
AUDIO CONTENT SEARCHING IN MULTI-MEDIA - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240013801 titled 'AUDIO CONTENT SEARCHING IN MULTI-MEDIA
Simplified Explanation
The patent application describes techniques for searching audio content in multimedia content, specifically audio and video evidence captured during an incident. Machine learning models can be trained to identify audio content portions and generate metadata tags automatically. These models can also track audio with specific characteristics across multiple multimedia content items. The processing of captured multimedia content can be done centrally at a network operations center (NOC) or at the network's edge, such as a body-worn camera or in-vehicle computer of a law enforcement vehicle.
- Machine learning models can be trained to identify and tag audio content portions in multimedia content.
- These models can track audio with specific characteristics across multiple multimedia content items.
- The processing of captured multimedia content can be done centrally at a network operations center (NOC) or at the network's edge, such as a body-worn camera or in-vehicle computer.
- The techniques aim to enhance investigator productivity during the review of captured multimedia content.
Potential Applications:
- Law enforcement agencies can use these techniques to efficiently search and review audio and video evidence captured during incidents.
- Media organizations can utilize these techniques to search and analyze audio content in multimedia files for various purposes, such as content categorization or transcription services.
Problems Solved:
- Searching and reviewing audio content in large amounts of multimedia content can be time-consuming and labor-intensive. These techniques aim to enhance investigator productivity by automating the identification and tagging of audio content portions.
- Tracking audio with specific characteristics across multiple multimedia content items can be challenging. Machine learning models can help solve this problem by learning and recognizing these characteristics.
Benefits:
- Increased efficiency and productivity for investigators and reviewers of multimedia content.
- Improved accuracy in identifying and tagging audio content portions.
- Enhanced search capabilities for audio content within multimedia files.
- Potential for automation and reduction of manual effort in processing and analyzing multimedia content.
Original Abstract Submitted
techniques for audio content searching in multi-media content are described. such techniques may be utilized to enhance investigator productivity while reviewing captured multi-media content, in particular, audio and video evidence captured during an incident. ml models may be trained to identify audio content portions and automatically generate metadata tags. ml models may be trained to track audio with a set of characteristics throughout a set of multi-media content items. ml models may be trained, and captured multi-media content may be processed centrally, for example, at a network operations center (noc). alternatively, or in addition, at least some model training and/or content processing may be performed at the network's edge, for example, performed by a content capturing device such as a body-worn camera and/or at a capture-local communications hub such as an in-vehicle computer of a law enforcement vehicle.
